Abstract: To help analytical chemists become tomorrow’s leaders, we must first examine the foundations of analytical sciences. Beyond chemical expertise, modern analytical chemistry rests on the pillars of applied physics and scientific computation. High-quality generative artificial intelligence (AI) can now serve as a tool for human innovators to discover, design, and develop more effective solutions to problems encountered in chemical analysis. Generative AI can also help reduce the perceived complexity of chemometric algorithms into manageable concepts that previously required months to master in the pre-AI era. This presentation proposes that generative AI can serve as a knowledgeable, Ph.D. level “colleague,” especially for analysis problems that require advanced signal processing and chemometrics. These challenges include seeking scientific advice on analytical problems; using AI to deepen historical literature searches; developing feature-detection methods; performing information-theoretic denoising; enhancing resolution through regularized deconvolution, which can increase resolution; and determining instrument transfer functions in spectroscopy and separation sciences. Examples will show how generative AI can help distill the key ideas from complex code, rendering it into a readily understandable explanation for analytical chemists. The second part will focus on unconventional uses of ChatGPT (Pro), ethical issues, and its role as an assistant for chemical analysis tasks, ranging from diagnosing issues in publications to reading non-English analytical literature that is otherwise neglected due to language barriers. Together, these advances show that, when used critically and with appropriate benchmark checks, generative AI can accelerate innovation and self-education in analytical chemistry. Unverified use of generative AI can yield deceptive results that appear like the correct answers from Clever Hans, the horse once thought to do complex arithmetic a century ago.
2025 Nobel Prize in Chemistry
Omar M. Yaghi is best known for developing metal–organic frameworks (MOFs) and pioneering reticular chemistry.
Omar M. Yaghi
Omar M. Yaghi received his Ph.D. in Chemistry from University of Illinois at Urbana-Champaign, and was an NSF Postdoctoral Fellow at Harvard University. He is the James and Neeltje Tretter Chair Professor of Chemistry at University of California, Berkeley. He is the Founding Director of the Berkeley Global Science Institute whose mission is to build centers of research in developing countries and provide opportunities for young scholars to discover and learn. He is also the Co-Director of the Kavli Energy NanoSciences Institute (Kavli ENSI) focusing on the basic science of energy transformation on the molecular level, the California Research Alliance by BASF (CARA) supporting joint academia-industry innovations, as well as the Bakar Institute of Digital Materials for the Planet (BIDMaP) which aims to develop cost-efficient, easily deployable versions of two classes of ultra porous materials – known as metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) – to help limit and address the impacts of climate change.
His work encompasses the synthesis, structure and properties of inorganic and organic compounds and the design and construction of new crystalline materials. He is widely known for pioneering several extensive classes of new materials: Metal-Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), and Zeolitic Imidazolate Frameworks (ZIFs). These materials have the highest surface areas known to date, making them useful for hydrogen and methane storage, carbon capture and conversion, water harvesting from desert air, and catalysis, to mention a few. The building block approach he developed has led to an exponential growth in the creation of new materials having a diversity and multiplicity previously unknown in chemistry. He termed this field ‘Reticular Chemistry’ and defines it as ‘stitching molecular building blocks into extended structures by strong bonds’. His work on MOFs, COFs, and ZIFs led to over 300 published articles, which have received a total of more than 250,000 citations and an h-index of 190.
Yaghi is an elected member of the U.S. National Academy of Sciences as well as the German National Academy of Sciences Leopoldina. He has been honored with awards from around the world, including the Sacconi Medal of the Italian Chemical Society (2004), Materials Research Society Medal (2007), American Chemical Society Award in the Chemistry of Materials (2009), Royal Society of Chemistry Centenary Prize (2010), King Faisal International Prize in Science (2015), Albert Einstein World Award of Science (2017), BBVA Foundation Frontiers of Knowledge Award (2017), Wolf Prize in Chemistry (2018), Eni Award for Excellence in Energy (2018), Gregori Aminoff Prize by the Royal Swedish Academy of Sciences (2019), August-Wilhelm-von-Hofmann-Denkmünze of the German Chemical Society (2020), Royal Society of Chemistry Sustainable Water Award (2020), VinFuture Prize (2021), Wilhelm Exner Medal (2023), Solvay Prize (2024), Tang Prize (2024), and Balzan Prize (2024).